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Introduction
(collapsed, click to expand)- Completed Appetite Whetting Part 1 (15:38)
- Completed Appetite Whetting Part 2 (13:44)
- Completed Context (9:30)
- Completed Dimensions (10:24)
- Completed This Course Part 1 (14:02)
- Completed This Course Part 2 (10:50)
- Completed eScience (11:46)
- Completed Big Data (14:36)
- Completed Guest Lecture: Biomedical Informatics (10:24)
- Completed Logistics (7:42)
- Completed Twitter Assignment: Getting Started with Problem 0 and Problem 1
Relational Databases, Relational Algebra
(collapsed, click to expand)- Completed From Data Models to Databases (10:35)
- Completed Motivating Relational Algebra (8:57)
- Completed Relational Algebra Introduction (10:58)
- Completed
Relational Algebra Details: Union, Diff, Select (10:53)
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- Completed
Relational Algebra Details: Project, Cross Product, Equi-Join (11:06)
011.6_relational_algebra_project_cross_equijoin.pdf for Relational Algebra Details: Project, Cross Product, Equi-Join (11:06)Subtitles (text) for Relational Algebra Details: Project, Cross Product, Equi-Join (11:06)Subtitles (srt) for Relational Algebra Details: Project, Cross Product, Equi-Join (11:06)Video (MP4) for Relational Algebra Details: Project, Cross Product, Equi-Join (11:06)
- Completed Relational Algebra Details: Theta-Join (8:34)
- Completed
SQL for Data Science: Interpreting Complicated SQL (12:12)
011.8_interpreting_complicated_sql.pdf for SQL for Data Science: Interpreting Complicated SQL (12:12)Subtitles (text) for SQL for Data Science: Interpreting Complicated SQL (12:12)Subtitles (srt) for SQL for Data Science: Interpreting Complicated SQL (12:12)Video (MP4) for SQL for Data Science: Interpreting Complicated SQL (12:12)
- Completed
SQL for Data Science: User-Defined Functions (7:59)
011.9_user_defined_functions.pdf for SQL for Data Science: User-Defined Functions (7:59)Subtitles (text) for SQL for Data Science: User-Defined Functions (7:59)Subtitles (srt) for SQL for Data Science: User-Defined Functions (7:59)Video (MP4) for SQL for Data Science: User-Defined Functions (7:59)
- Completed Physical Optimization (11:14)
- Completed Declarative Languages (10:30)
- Completed Logical Data Independence (11:23)
MapReduce
(collapsed, click to expand)- Completed Scalability Basics (16:18)
- Completed Parallel Processing Patterns (11:26)
- Completed MapReduce Abstractions (11:17)
- Completed MapReduce Pseudocode (7:54)
- Completed MapReduce Text Examples (9:58)
- Completed
MapReduce Relational Join, Social Example (13:17)
020_map_reduce_join_social_examples.pdf for MapReduce Relational Join, Social Example (13:17)Subtitles (text) for MapReduce Relational Join, Social Example (13:17)Subtitles (srt) for MapReduce Relational Join, Social Example (13:17)Video (MP4) for MapReduce Relational Join, Social Example (13:17)
- Completed MapReduce Matrix Multiply Example (9:31)
- Completed MapReduce Implementation Overview (13:38)
- Completed Parallel Databases (16:18)
- Completed Comparing MapReduce and Databases (06:39)
- Completed Experimental Results: MR and DB (15:01)
NoSQL
(collapsed, click to expand)- Completed NoSQL Introduction (8:30)
- Completed Eventual Consistency (18:56)
- Completed Example: Memcached (16:37)
- Completed Example: Dynamo (10:16)
- Completed Example: CouchDB (10:00)
- Completed Example: BigTable (11:05)
- Completed Example: Other Google Systems (16:18)
- Completed Response to NoSQL Systems (14:44)
- Completed Pig Intro (12:02)
- Completed Pig Functions (11:41)
- Completed Pig Join and Co-Group Join (16:10)
- Completed Pig Evaluation (10:11)
Basic Statistical Analysis
(collapsed, click to expand)- Completed Statistics Intro (10:36)
- Completed Publication Bias (8:45)
- Completed
Effect Size, Meta-analysis, Heteroskedasticity (9:31)
040_effect_size_meta_analysis_heteroskedasticity.pdf for Effect Size, Meta-analysis, Heteroskedasticity (9:31)Subtitles (text) for Effect Size, Meta-analysis, Heteroskedasticity (9:31)Subtitles (srt) for Effect Size, Meta-analysis, Heteroskedasticity (9:31)Video (MP4) for Effect Size, Meta-analysis, Heteroskedasticity (9:31)
- Completed Fraud and Benfords Law (10:55)
- Completed Multiple Hypothesis Testing (11:22)
- Completed Recap and Big Data (11:39)
- Completed Bayesian Intro (7:59)
- Completed Bayes Rule (11:53)
Topics in Machine Learning, Part 1
(collapsed, click to expand)- Completed 01 Introduction to Machine Learning Part 1 (07:54)
- Completed 02 Introduction to Machine Learning Part 2 (05:23)
- Completed 03 Rules Part 1 (09:19)
- Completed 04 Rules Part 2 (05:39)
- Completed 05 Decision Trees & Entropy (10:51)
- Completed 06 Information Gain (11:43)
- Completed 07 Overfitting (11:04)
- Completed 08 Evaluation and Cross-Validation (10:46)
- Completed 09 The Bootstrap (04:13)
- Completed 10 Ensembles, Bagging, and Boosting (09:19)
- Completed 11 Random Forests (11:16)
- Completed 12 k Nearest Neighbors (11:43)
Topics in Machine Learning, Part 2
(collapsed, click to expand)- Completed 01 Gradient Descent Part 1 (07:18)
- Completed 02 Gradient Descent Part 2 (06:29)
- Completed
03 Intuition for Logistic Regression and Support Vector Machines (10:55)
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- Completed 04 Intuition for Regularization (06:59)
- Completed
05 Stochastic Gradient Descent, Minibatches, Parallelization (08:53)
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- Completed 06 Unsupervised Learning (06:11)
- Completed 07 K-means (05:56)
- Completed 08 DBSCAN (09:13)
Visualization
(collapsed, click to expand)- Completed 01 Introduction (7:17)
- Completed 02 Data Types (9:37)
- Completed 03 Data Types (Exercises) (4:07)
- Completed 04 Data Dimensions (3:08)
- Completed 05 Visual Encoding (Part 1) (6:38)
- Completed 06 Visual Encoding (Part 2) (2:54)
- Completed 07 Visual Perception (Part 1) (4:39)
- Completed 08 Visual Perception (Part 2) (4:18)
- Completed 09 Visual Perception (Part 3) (3:56)
- Completed 10 Evaluation (3:25)
Graph Analytics
(collapsed, click to expand)- Completed 01 Graph Basics (06:22)
- Completed 02 Structure: Degree Histograms (08:14)
- Completed 03 Structure: Diameter, Connectivity, Centrality (06:56)
- Completed 04 Traversal: PageRank (06:37)
- Completed 05 Traversal: Spanning Trees, Circuits, Flows (06:57)
- Completed 06 Patterns: Triangles, SPARQL, Datalog (10:02)
- Completed 07 Patterns: Relational Algebra for Graph Query (08:26)
- Completed 08 PRISM Example in Datalog (11:10)
- Completed 09 Evaluating Graph Traversal Queries (08:29)
- Completed 10 Optimizing MapReduce for Graph Traversal (08:20)
- Completed 11 Graph Representations (06:51)
- Completed 12 PageRank in MapReduce and Pregel (10:42)
Perspectives Beyond MapReduce
(collapsed, click to expand)- Completed 01 Guest Segment, Aaron Kimball, Wibidata
- Completed 02 Guest Segment, Karen Hsu, Datameer